Effective mathematical modelling of health passes during a pandemic

Stefan Hohenegger, Giacomo Cacciapaglia*, Francesco Sannino


Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

30 Downloads (Pure)


We study the impact on the epidemiological dynamics of a class of restrictive measures that are aimed at reducing the number of contacts of individuals who have a higher risk of being infected with a transmittable disease. Such measures are currently either implemented or at least discussed in numerous countries worldwide to ward off a potential new wave of COVID-19. They come in the form of Health Passes (HP), which grant full access to public life only to individuals with a certificate that proves that they have either been fully vaccinated, have recovered from a previous infection or have recently tested negative to SARS-Cov-2. We develop both a compartmental model as well as an epidemic Renormalisation Group approach, which is capable of describing the dynamics over a longer period of time, notably an entire epidemiological wave. Introducing different versions of HPs in this model, we are capable of providing quantitative estimates on the effectiveness of the underlying measures as a function of the fraction of the population that is vaccinated and the vaccination rate. We apply our models to the latest COVID-19 wave in several European countries, notably Germany and Austria, which validate our theoretical findings.

TidsskriftScientific Reports
Antal sider13
StatusUdgivet - 28. apr. 2022

Bibliografisk note

Publisher Copyright:
© 2022, The Author(s).


Dyk ned i forskningsemnerne om 'Effective mathematical modelling of health passes during a pandemic'. Sammen danner de et unikt fingeraftryk.